September 2017

In Jamaica, about a quarter of electricity produced is stolen or “lost” through non-paying customers and/or accounting errors. Manual detection has failed to make a difference in reducing this theft.

ESMAP’s technical assistance team implemented a machine learning model to help Jamaican utility JPS identify and decrease incidents of theft.

The machine learning model is based on an open source code, and is available for free to any utility.

About a quarter of the electricity produced by Jamaica’s energy utility, Jamaica Public Service (JPS) is stolen. When traditional, labor-intensive methods failed to produce lasting results, Jamaica tried a different approach: machine learning.

Globally, billions of dollars are lost every year due to electricity theft, wherein electricity is distributed to customers but is never paid for. In 2014 alone, Jamaica’s total power transmission and distribution system reported 27% of losses (due to technical and non-technical reasons), close to double the regional average. While the utility company absorbs a portion of the cost, it also passes some of that cost onto consumers. Both actors therefore have an incentive to want to change this.

To combat this, JPS would spend more than $10 million (USD) on anti-theft measures every year, only to see theft numbers temporarily dip before climbing back up again. The problem was, these measures relied primarily on human-intensive, manual detection, and customers stealing electricity used more and more sophisticated ways to go around regularly metered use. JPS employees would use their institutional knowledge of serial offenders and would spend hours poring over metering data to uncover irregular patterns in electricity usage to identify shady accounts. But it wasn’t enough to effectively quash incidents of theft.

Pension funds are rightly viewed as an important source of long-term capital in many countries. Following the global financial crisis of 2008, the theme of long-term investment and the role of institutional investors as providers of domestic capital for economic development has been high on policy makers’ agendas. Despite generally positive findings linking pension system development and economic growth, there are also plenty of disappointments. In too many countries, pension fund investments remain highly concentrated in bank deposits and traditional government bonds. This lack of diversification can be explained by many factors, for instance, unsupportive macro conditions, shortage of investment instruments, poor governance, limited investment knowledge, and regulations with restrictive asset class limits and excessive reliance on short-term performance monitoring.

We know that fiscal policy can be harnessed to reduce inequality in low- and middle-income countries, but until now, we knew less about its ability to reduce poverty. Our recent volume looks at the revenue and spending of governments across eight low and middle income countries (Armenia, Ethiopia, Georgia, Indonesia, Jordan, Russia, South Africa and Sri Lanka), and it reveals that fiscal systems, while nearly always reducing inequality, can often worsen poverty.

The world is urbanizing fast—200,000 people are moving to cities every day in search of homes, jobs, as well as education and healthcare services for their families. Supporting this influx with proper infrastructure and services for water, sanitation, transport, and green spaces will require an estimated $1 trillion each year.

This is the first in a potential new series of posts of short interviews with development economists. Chris Udry was one of the pioneers of doing detailed fieldwork in development as a grad student and has continued to be one of the most respected leaders in the profession. While at Yale he taught David, and advised both David and Markus, and is famous for the amount of time he puts into his grad students. Most recently he has moved from Yale to Northwestern. We thought this might be a good time for him to reflect on his approach to teaching and advising, and to share his thoughts on some of the emerging issues/trends in development economics.

Let’s start with your approach to teaching development economics at the graduate level. The class when you taught David in 1999 was heavy on the agricultural household model and understanding micro development through different types of market failures. Most classes would involve in-depth discussion of one or at most two papers, with a student assigned most weeks to lead this discussion. There was a lot of discussion of the empirical methods in different papers, but no replication tasks and the only empirical work was as part of a term paper. How has your approach to teaching development changed (or not) since this time?

Try as I might, I have made little progress on changing my basic approach to teaching. The papers and topics have changed, but the essence of my graduate teaching remains the in-depth discussion of a paper or two each class. I’ve tried to expand the use of problem sets, and had a number of years of replication assignments. The first was hindered by my own inadequate energy (it’s hard making up decent questions!). I found that replication exercises required too much time and effort in data cleaning by students relative to their learning gain. Students were spending too much time cleaning, merging and recreating variables and too little time thinking about the ideas in the paper. I’ll reassess assigning replication this year, because there may now be enough well-documented replication datasets and programs available. With these as a starting point, it would be possible to get quickly into substantive issues in the context of a replication.

The recent debate on whether it makes more sense to measure Gross Domestic Product (GDP) in Ringgit or in Dollars is a healthy one. It reflects a sound interest by many segments of Malaysian society in statistics that measure economic development and how it changes people’s living standards. This is the fundamental question: what does GDP really mean in the daily life of Malaysians. There are sound arguments on both sides and, in a way, both are right, depending on what perspective is taken.

The World Bank partnered with the Women’s Media Center “Let’s Talk Money” radio show to help build financial stability in Cambodia.

Risky financial behaviors among Cambodians of the post-millennial generation have become more widespread in the country, especially among the 18-35 age group. While they are important customers for the financial and banking sectors, their behaviors are often dominated by lavish spending and excessive borrowing.

Africa has the world’s least developed weather, water, and climate observation network, with half of its surface weather stations not reporting accurate data. Hydrological and meteorological (“hydromet”) hazards are responsible for 90% of total disaster losses worldwide. Being able to understand, predict, and warn citizens about natural hazards and disasters drives the ability of governments to reduce economic risks and save lives.

Income growth is not the sole aim of economic development. An equally important, albeit harder to quantify objective is a sense of progress for the entire community, and a confidence that prosperity is sustainable and shared equitably across society for the long term.